4 citations · 4 across the 5 of their papers we have counts for
6 papers
FlexiAvatar: Unified 3D Gaussian Human Avatars Under Arbitrary Body Visibility
Yihalem Yimolal Tiruneh, Muhammad Salman Ali, Uyoung Jeong +5
Reconstructing animatable 3D human avatars from monocular video is a fundamental problem in computer vision with broad applications in AR/VR and digital content creation. Existing…
THOM: Generating Physically Plausible Hand-Object Meshes From Text
Uyoung Jeong, Yihalem Yimolal Tiruneh, Hyung Jin Chang +2
Generating photorealistic 3D hand-object interactions (HOIs) from text is important for applications like robotic grasping and AR/VR content creation. In practice, however, achievi…
HandVQA: Diagnosing and Improving Fine-Grained Spatial Reasoning about Hands in Vision-Language Models
MD Khalequzzaman Chowdhury Sayem, Mubarrat Tajoar Chowdhury, Yihalem Yimolal Tiruneh +4
Understanding the fine-grained articulation of human hands is critical in high-stakes settings such as robot-assisted surgery, chip manufacturing, and AR/VR-based human-AI interact…
QORT-Former: Query-optimized Real-time Transformer for Understanding Two Hands Manipulating Objects
Elkhan Ismayilzada, MD Khalequzzaman Chowdhury Sayem, Yihalem Yimolal Tiruneh +3
Significant advancements have been achieved in the realm of understanding poses and interactions of two hands manipulating an object. The emergence of augmented reality (AR) and vi…
SDDGR: Stable Diffusion-based Deep Generative Replay for Class Incremental Object Detection
Junsu Kim, Hoseong Cho, Jihyeon Kim +2
In the field of class incremental learning (CIL), generative replay has become increasingly prominent as a method to mitigate the catastrophic forgetting, alongside the continuous…
Class-Wise Buffer Management for Incremental Object Detection: An Effective Buffer Training Strategy
Junsu Kim, Sumin Hong, Chanwoo Kim +6
Class incremental learning aims to solve a problem that arises when continuously adding unseen class instances to an existing model This approach has been extensively studied in th…